Skip to main content

Quickly import reference data sets for navigation system design and testing.

Project description

Organic Navigation Reference Data

The purpose of the onvadata module is to make reference data sets easily accessible for the design, development, and testing of navigation algorithms. The defining characteristic of reference data sets are that they are well understood, documented, and purged of data logging artifacts.

Quick Start

List Data Available

All data sets are referenced using their shortname.

>> import onavdata
>> onavdata.print_shortnames()
	 2011 UMN-UAV GPSFASER1
	 2012 UMN-UAV FASER5
	 2012 UMN-UAV GPSFASER3
	 2012 UMN-UAV THOR79
	 2012 UMN-UAV THOR77
	 2012 UMN-UAV THOR75
	 2012 UMN-UAV THOR60
	 SIM-PERFECT-CAR NORTH VARY-SPEED FIXED-HEADING
	 SIM-MEASURED-CAR NORTH VARY-SPEED FIXED-HEADING
	 SIM-PERFECT-CAR NORTH VARY-SPEED VARY-HEADING
	 SIM-MEASURED-CAR NORTH VARY-SPEED VARY-HEADING
	 SIM-PERFECT-CAR NORTH FIXED-SPEED VARY-HEADING
	 SIM-MEASURED-CAR NORTH FIXED-SPEED VARY-HEADING
	 SIM-PERFECT-CAR NORTH FIXED-SPEED FIXED-HEADING
	 SIM-MEASURED-CAR NORTH FIXED-SPEED FIXED-HEADING

Load a Reference Data Set

An abitrary data set can be loaded if no shortname is specified. In this case the data from 2014 UMN-UAV THOR77 was returned.

>> import onavdata
>> df = onavdata.get_data()
	get_data(): No shortname specified so choice will be arbitrary.  Returning: 2014 UMN-UAV THOR77
>> df.head()
		           AccelX (m/s^2)  AccelY (m/s^2)  AccelZ (m/s^2)       ...         AngleHeading (rad)  AnglePitch (rad)  AngleRoll (rad)
	TimeFromStart (s)                                                       ...
	0.00                     1.862795       -0.392167       -9.673463       ...                   1.004700          0.192806         0.006130
	0.02                     1.895476       -0.424848       -9.640783       ...                   1.004225          0.192856         0.006130
	0.04                     1.895476       -0.359487       -9.706145       ...                   1.003786          0.192888         0.006259
	0.06                     1.895476       -0.392167       -9.640783       ...                   1.003258          0.192990         0.006354
	0.08                     1.895476       -0.392167       -9.640783       ...                   1.002907          0.193056         0.006482

	[5 rows x 12 columns]

This module manages easy access to multiple navigation-sensor data sets.

Meta Data Supported

Sampling Time

TODO

Rename Data Columns

TODO

Transformation from sensor-frame to body-frame

Transformation matrices can be defined under the table heading [Rsensor2body]. The subsequent key/value pairs will define the prefix of the sensor column followed by the rotation matrix. Since the transformation is applied AFTER any column renaming (see above), the renamed column entires must be used.

Example

docs/map-chip-to-body.png The above transformation can be defined for the accelerometer columns. Assuming our accelerometer columns are:

['AccelX (m/s^2)', 'AccelY (m/s^2)', 'AccelZ (m/s^2)']

We define the following associated meta data entry:

[Rsensor2body]
Accel = [[ 0, -1,  0], 
         [-1,  0,  0],
         [ 0,  0, -1]]

The module will automatically find the associated columns with the Accel prefix and apply the defined rotation matrix.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for onavdata, version 0.0.7
Filename, size File type Python version Upload date Hashes
Filename, size onavdata-0.0.7-py3-none-any.whl (15.2 MB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size onavdata-0.0.7.tar.gz (15.2 MB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page